Carlos F. Lopez, Ph.D.

Carlos F. Lopez received his B.Sc., and B.L.A. degrees from the University of Miami (Coral Gables, Florida) and his Ph.D. in Physical Chemistry from the University of Pennsylvania (Philadelphia, PA). He pursued a Postdoctoral Fellowship at the University of Texas at Austin (Austin, TX) where he studied theoretical biophysics and followed this with a postdoctoral position at Harvard Medical School (Boston, MA).

He moved to Vanderbilt University School of Medicine (Nashville, TN) in late 2012 as an Assistant Professor of Cancer Biology and member of the Vanderbilt-Ingram Cancer Center the Center for Quantitative Sciences. He has been the recipient of several awards, honors, and fellowships including multiple Minority Supplement Awards from NIH, Phi Lambda Upsilon Academic Honor Society “Best Graduating Senior”(1998), South Florida American Chemical Society Excellence in Undergraduate Research(1998), American Institute of Chemists Outstanding Senior Award(1999), King Trust (The Medical Foundation) / H. W. Pierce Postdoctoral Research Fellowship (2008), NIH K22 Transition Career Development Award, American Association for Cancer Research – Minority Scholar in Cancer Research Award (2012), UK – US Collaboration Development Award (2012), and Vanderbilt-Ingram Cancer Center Young Ambassadors Award (2013).

His work develops and applies novel computational modeling tools and leverages strong experimental collaborations to describe intracellular biochemical signaling networks using a wide range of mathematical methods and further our understanding of cellular decision-making processes. This work could lead to a better understanding of dynamic cellular systems, how they are regulated in health, dysregulated in diseases such as cancer, and use this knowledge to guide experiments toward novel therapies. His goal is to develop a predictive theoretical foundation to explain how systems-level biochemical interaction networks process biochemical signals and lead to a phenotypic outcome. Professor Lopez is ideally positioned to bring a new era of mathematical modeling of living systems to the biological and physical sciences mainstream. His work could yield the first physical-law based predictive models of biological signaling processes that could be used to understand how cells respond to perturbations. With this knowledge it would be possible to manipulate microorganisms for biological engineering and develop targeted cancer treatments for personalized medicine.